Johnathan M. Bardsley

发表

A Variational Approach to Video Segmentation for Botanical Data

Aaron Luttman, Johnathan M. Bardsley, J. Bardsley, 2007, SIAM J. Sci. Comput..

MCMC Algorithms for Computational UQ of Nonnegativity Constrained Linear Inverse Problems

Per Christian Hansen, Johnathan M. Bardsley, P. Hansen, 2020, SIAM J. Sci. Comput..

A Bound-and Equality-Constrained Quadratic Programming Method for Image Reconstruction

Johnathan M. Bardsley, Marylesa Howard, 2015 .

Wavefront Reconstruction Methods for Adaptive Optics Systems on Ground-Based Telescopes

Johnathan M. Bardsley, J. Bardsley, 2008, SIAM J. Matrix Anal. Appl..

A Nonnegatively Constrained Convex Programming Method for Image Reconstruction

Johnathan M. Bardsley, Curtis R. Vogel, C. Vogel, 2003, SIAM J. Sci. Comput..

Total variation-penalized Poisson likelihood estimation for ill-posed problems

Aaron Luttman, Johnathan M. Bardsley, J. Bardsley, 2009, Adv. Comput. Math..

MCMC-Based Image Reconstruction with Uncertainty Quantification

Johnathan M. Bardsley, J. Bardsley, 2012, SIAM J. Sci. Comput..

L 1 -Regularized Inverse Problems for Image Deblurring via Bound- and Equality-Constrained Optimization

Johnathan M. Bardsley, Marylesa Howard, J. Bardsley, 2018 .

Covariance-Preconditioned Iterative Methods for Nonnegatively Constrained Astronomical Imaging

James G. Nagy, Johnathan M. Bardsley, J. Nagy, 2005, SIAM J. Matrix Anal. Appl..

Bayesian Inverse Problems with l1 Priors: A Randomize-Then-Optimize Approach

Zheng Wang, Tiangang Cui, Johnathan M. Bardsley, 2016, SIAM J. Sci. Comput..

Bayesian Inverse Problems with L[subscript 1] Priors: A Randomize-Then-Optimize Approach

Tiangang Cui, Zheng Wang, Johnathan M. Bardsley, 2017 .

MATLAB Software for Supervised Classication in Remote Sensing and Image Processing

Johnathan M. Bardsley, Marylesa Howard, Mark S. Lorang, 2012 .

An Iterative Method for Edge-Preserving MAP Estimation When Data-Noise Is Poisson

Johnathan M. Bardsley, John Goldes, 2010, SIAM J. Sci. Comput..

Randomize-Then-Optimize for Sampling and Uncertainty Quantification in Electrical Impedance Tomography

Jari P. Kaipio, Heikki Haario, Johnathan M. Bardsley, 2015, SIAM/ASA J. Uncertain. Quantification.

Point Spread Function Estimation in X-Ray Imaging with Partially Collapsed Gibbs Sampling

Aaron Luttman, Johnathan M. Bardsley, Kevin T. Joyce, 2017, SIAM J. Sci. Comput..

Erratum: A Variational Approach to Video Segmentation for Botanical Data

Aaron Luttman, Johnathan M. Bardsley, J. Bardsley, 2007, SIAM J. Sci. Comput..

An Efficient Phase and Object Estimation Scheme for Phase-Diversity Time Series Data

Johnathan M. Bardsley, J. Bardsley, 2008, IEEE Transactions on Image Processing.

Randomize-Then-Optimize: A Method for Sampling from Posterior Distributions in Nonlinear Inverse Problems

Heikki Haario, Johnathan M. Bardsley, Marko Laine, 2014, SIAM J. Sci. Comput..

Semivariogram methods for modeling Whittle–Matérn priors in Bayesian inverse problems

Tiangang Cui, Johnathan M. Bardsley, Richard D. Brown, 2018, Inverse Problems.

Regularization parameter selection and an efficient algorithm for total variation-regularized positron emission tomography

Johnathan M. Bardsley, John Goldes, 2010, Numerical Algorithms.

Quantifying Uncertainties in Inverse Problems: Meaning and Usefulness of Error Bars on Information Extracted from Stockpile Stewardship Experiments

Johnathan M. Bardsley, Marylesa Howard, Aaron Luttman, 2015 .

Structured linear algebra problems in adaptive optics imaging

James G. Nagy, Sarah Knepper, Johnathan M. Bardsley, 2011, Adv. Comput. Math..

RESEARCH ARTICLE An MCMC Method for Uncertainty Quantication in Nonnegativity Constrained Inverse Problems

Johnathan M. Bardsley, Colin Fox, 2011 .

Krylov space approximate Kalman filtering

Johnathan M. Bardsley, Marylesa Howard, Antti Solonen, 2013, Numer. Linear Algebra Appl..

Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes

Mickaël Binois, Johnathan M. Bardsley, Matthias Chung, 2018, 1802.00852.

Analysis of the Gibbs Sampler for Hierarchical Inverse Problems

Andrew M. Stuart, Johnathan M. Bardsley, Omiros Papaspiliopoulos, 2013, SIAM/ASA J. Uncertain. Quantification.

Optimization-Based Markov Chain Monte Carlo Methods for Nonlinear Hierarchical Statistical Inverse Problems

Tiangang Cui, Johnathan M. Bardsley, 2021, SIAM/ASA J. Uncertain. Quantification.

A Hybrid Gibbs Sampler for Edge-Preserving Tomographic Reconstruction with Uncertain View Angles

Yiqiu Dong, Per Christian Hansen, Johnathan M. Bardsley, 2021, SIAM/ASA J. Uncertain. Quantification.

Stopping rules for a nonnegatively constrained iterative method for ill-posed Poisson imaging problems

Johnathan M. Bardsley, J. Bardsley, 2008 .

Tikhonov Regularization for Ill-Posed Poisson Likelihood Estimation: Analysis and Computation

Johnathan M. Bardsley, J. Bardsley, 2006 .

Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation

Johnathan M. Bardsley, John Goldes, J. Bardsley, 2009 .

LARGE-SCALE KALMAN FILTERING USING THE LIMITED MEMORY BFGS METHOD

Heikki Haario, Tuomo Kauranne, Johnathan M. Bardsley, 2009 .

A NONNEGATIVELY CONSTRAINED TRUST REGION ALGORITHM FOR THE RESTORATION OF IMAGES WITH AN UNKNOWN BLUR

Johnathan M. Bardsley, 2005 .

A theoretical framework for the regularization of Poisson likelihood estimation problems

Johnathan M. Bardsley, J. Bardsley, 2010 .

The variational Kalman filter and an efficient implementation using limited memory BFGS

Heikki Haario, Tuomo Kauranne, Johnathan M. Bardsley, 2010 .

OPTIMIZATION-BASED SAMPLING IN ENSEMBLE KALMAN FILTERING

Heikki Haario, Johnathan M. Bardsley, Antti Solonen, 2014 .

Computational methods for a large-scale inverse problem arising in atmospheric optics

Johnathan M. Bardsley, Luc Gilles, Curt Vogel, 2002 .

Techniques for regularization parameter and hyper-parameter selection in PET and SPECT imaging

Johnathan M. Bardsley, John Goldes, John Goldes, 2011 .

A METROPOLIS-HASTINGS METHOD FOR LINEAR INVERSE PROBLEMS WITH POISSON LIKELIHOOD AND GAUSSIAN PRIOR

Aaron Luttman, Johnathan M. Bardsley, J. Bardsley, 2016 .

An efficient computational method for total variation-penalized Poisson likelihood estimation

Johnathan M. Bardsley, J. Bardsley, 2008 .

An MCMC method for uncertainty quantification in nonnegativity constrained inverse problems

Johnathan M. Bardsley, Colin Fox, C. Fox, 2012 .

Dealing with edge effects in least-squares image deconvolution problems

Marco Donatelli, Johnathan M. Bardsley, Willem Wamsteker, 2005 .

Gaussian Markov random field priors for inverse problems

Johnathan M. Bardsley, J. Bardsley, 2013 .

Optimization-Based MCMC Methods for Nonlinear Hierarchical Statistical Inverse Problems pdf

Tiangang Cui, Johnathan M. Bardsley, Johnathan Bardsley, 2020, ArXiv.

Scalable Optimization-Based Sampling on Function Space

Tiangang Cui, Zheng Wang, Johnathan M. Bardsley, 2019, SIAM J. Sci. Comput..

A Parametric Bootstrap Method for Uncertainty Quantification in Ill-Posed , Inverse Problems with Poisson Noise

Johnathan M. Bardsley, H. Haario, J. Bardsley, 2013 .

Hierarchical regularization for edge-preserving reconstruction of PET images

Johnathan M. Bardsley, D. Calvetti, E. Somersalo, 2010 .

A computational method for the restoration of images with an unknown, spatially-varying blur.

Stuart Jefferies, Johnathan M. Bardsley, James Nagy, 2006, Optics express.

THE STABILIZING PROPERTIES OF NONNEGATIVITY CONSTRAINTS IN LEAST-SQUARES IMAGE RECONSTRUCTION

Johnathan M. Bardsley, J. Merikoski, J. Bardsley, 2007 .

APPLICATIONS OF A NONNEGATIVELY CONSTRAINED ITERATIVE METHOD WITH STATISTICALLY BASED STOPPING RULES TO CT, PET, AND SPECT IMAGING

Johnathan M. Bardsley, J. Bardsley, 2011 .

A NONNEGATIVELY CONSTRAINED ITERATIVE METHOD WITH STATISTICALLY BASED STOPPING RULES FOR CT , PET , AND SPECT IMAGING

Johnathan M. Bardsley, J. Bardsley, 2010 .

AN NONNEGATIVELY CONSTRAINED ITERATIVE METHOD FOR POSITRON EMISSION TOMOGRAPHY

Johnathan M. Bardsley, J. Bardsley, 2009 .

Laplace-distributed increments, the Laplace prior, and edge-preserving regularization

Johnathan M. Bardsley, J. Bardsley, 2012 .

DEBLURRING , GAUSSIAN MARKOV RANDOM FIELDS , AND NEUMANN BOUNDARY CONDITIONS

Johnathan M. Bardsley, J. Nagy, J. Bardsley, 2012 .

TR-2012-012 Image Deblurring , Gaussian Markov Random Fields , and Neumann Boundary Conditions

Johnathan M. Bardsley, J. Nagy, J. Bardsley, 2012 .

Regularization parameter selection for penalized-maximum likelihood methods in PET

Johnathan M. Bardsley, J. Bardsley, John Goldes, 2010 .

An Efficient MCMC Method for Uncertainty Quantification in Inverse Problems

Johnathan M. Bardsley, J. Bardsley, 2010 .

Parameter identification for a dispersive dielectric in 2D electromagnetics: forward and inverse methodology with statistical considerations

Johnathan M. Bardsley, H. Banks, 2003 .